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        <a href="#definition">definition</a> - <a href="#mistake">mistake</a> -
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        <a href="#code">code</a>
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<div id="definition" class="section level1">
<h1>Definition</h1>
<hr />
<p>A <code>heatmap</code> is a graphical representation of data where
the individual values contained in a <strong>matrix</strong> are
represented as colors. It is a bit like looking a data table from
above.</p>
<p>Here is an example showing 8 general features like population or life
expectancy for about 30 countries in 2015. Data come from the French
National Institute of <a
href="https://www.ined.fr/en/everything_about_population/data/all-countries/?lst_continent=908&amp;lst_pays=926">Demographic
Studies</a>.</p>
<div class="sourceCode" id="cb1"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb1-1"><a href="#cb1-1" tabindex="-1"></a><span class="co"># Libraries</span></span>
<span id="cb1-2"><a href="#cb1-2" tabindex="-1"></a><span class="fu">library</span>(tidyverse)</span>
<span id="cb1-3"><a href="#cb1-3" tabindex="-1"></a><span class="fu">library</span>(hrbrthemes)</span>
<span id="cb1-4"><a href="#cb1-4" tabindex="-1"></a><span class="fu">library</span>(viridis)</span>
<span id="cb1-5"><a href="#cb1-5" tabindex="-1"></a><span class="fu">library</span>(plotly)</span>
<span id="cb1-6"><a href="#cb1-6" tabindex="-1"></a><span class="co"># d3heatmap is not on CRAN yet, but can be found here: https://github.com/talgalili/d3heatmap</span></span>
<span id="cb1-7"><a href="#cb1-7" tabindex="-1"></a><span class="fu">library</span>(d3heatmap)</span>
<span id="cb1-8"><a href="#cb1-8" tabindex="-1"></a></span>
<span id="cb1-9"><a href="#cb1-9" tabindex="-1"></a><span class="co"># Load data</span></span>
<span id="cb1-10"><a href="#cb1-10" tabindex="-1"></a>data <span class="ot">&lt;-</span> <span class="fu">read.table</span>(<span class="st">&quot;https://raw.githubusercontent.com/holtzy/data_to_viz/master/Example_dataset/multivariate.csv&quot;</span>, <span class="at">header =</span> T, <span class="at">sep =</span> <span class="st">&quot;;&quot;</span>)</span>
<span id="cb1-11"><a href="#cb1-11" tabindex="-1"></a><span class="fu">colnames</span>(data) <span class="ot">&lt;-</span> <span class="fu">gsub</span>(<span class="st">&quot;</span><span class="sc">\\</span><span class="st">.&quot;</span>, <span class="st">&quot; &quot;</span>, <span class="fu">colnames</span>(data))</span>
<span id="cb1-12"><a href="#cb1-12" tabindex="-1"></a></span>
<span id="cb1-13"><a href="#cb1-13" tabindex="-1"></a><span class="co"># Select a few country</span></span>
<span id="cb1-14"><a href="#cb1-14" tabindex="-1"></a>data <span class="ot">&lt;-</span> data <span class="sc">%&gt;%</span></span>
<span id="cb1-15"><a href="#cb1-15" tabindex="-1"></a>  <span class="fu">filter</span>(Country <span class="sc">%in%</span> <span class="fu">c</span>(<span class="st">&quot;France&quot;</span>, <span class="st">&quot;Sweden&quot;</span>, <span class="st">&quot;Italy&quot;</span>, <span class="st">&quot;Spain&quot;</span>, <span class="st">&quot;England&quot;</span>, <span class="st">&quot;Portugal&quot;</span>, <span class="st">&quot;Greece&quot;</span>, <span class="st">&quot;Peru&quot;</span>, <span class="st">&quot;Chile&quot;</span>, <span class="st">&quot;Brazil&quot;</span>, <span class="st">&quot;Argentina&quot;</span>, <span class="st">&quot;Bolivia&quot;</span>, <span class="st">&quot;Venezuela&quot;</span>, <span class="st">&quot;Australia&quot;</span>, <span class="st">&quot;New Zealand&quot;</span>, <span class="st">&quot;Fiji&quot;</span>, <span class="st">&quot;China&quot;</span>, <span class="st">&quot;India&quot;</span>, <span class="st">&quot;Thailand&quot;</span>, <span class="st">&quot;Afghanistan&quot;</span>, <span class="st">&quot;Bangladesh&quot;</span>, <span class="st">&quot;United States of America&quot;</span>, <span class="st">&quot;Canada&quot;</span>, <span class="st">&quot;Burundi&quot;</span>, <span class="st">&quot;Angola&quot;</span>, <span class="st">&quot;Kenya&quot;</span>, <span class="st">&quot;Togo&quot;</span>)) <span class="sc">%&gt;%</span></span>
<span id="cb1-16"><a href="#cb1-16" tabindex="-1"></a>  <span class="fu">arrange</span>(Country) <span class="sc">%&gt;%</span></span>
<span id="cb1-17"><a href="#cb1-17" tabindex="-1"></a>  <span class="fu">mutate</span>(<span class="at">Country =</span> <span class="fu">factor</span>(Country, Country))</span>
<span id="cb1-18"><a href="#cb1-18" tabindex="-1"></a></span>
<span id="cb1-19"><a href="#cb1-19" tabindex="-1"></a><span class="co"># Matrix format</span></span>
<span id="cb1-20"><a href="#cb1-20" tabindex="-1"></a>mat <span class="ot">&lt;-</span> data</span>
<span id="cb1-21"><a href="#cb1-21" tabindex="-1"></a><span class="fu">rownames</span>(mat) <span class="ot">&lt;-</span> mat[,<span class="dv">1</span>]</span>
<span id="cb1-22"><a href="#cb1-22" tabindex="-1"></a>mat <span class="ot">&lt;-</span> mat <span class="sc">%&gt;%</span> dplyr<span class="sc">::</span><span class="fu">select</span>(<span class="sc">-</span>Country, <span class="sc">-</span>Group, <span class="sc">-</span>Continent)</span>
<span id="cb1-23"><a href="#cb1-23" tabindex="-1"></a>mat <span class="ot">&lt;-</span> <span class="fu">as.matrix</span>(mat)</span>
<span id="cb1-24"><a href="#cb1-24" tabindex="-1"></a></span>
<span id="cb1-25"><a href="#cb1-25" tabindex="-1"></a><span class="co"># Heatmap</span></span>
<span id="cb1-26"><a href="#cb1-26" tabindex="-1"></a><span class="co">#d3heatmap(mat, scale=&quot;column&quot;, dendrogram = &quot;none&quot;, width=&quot;800px&quot;, height=&quot;80Opx&quot;, colors = &quot;Blues&quot;)</span></span>
<span id="cb1-27"><a href="#cb1-27" tabindex="-1"></a></span>
<span id="cb1-28"><a href="#cb1-28" tabindex="-1"></a><span class="fu">library</span>(heatmaply)</span>
<span id="cb1-29"><a href="#cb1-29" tabindex="-1"></a>p <span class="ot">&lt;-</span> <span class="fu">heatmaply</span>(mat,</span>
<span id="cb1-30"><a href="#cb1-30" tabindex="-1"></a>        <span class="at">dendrogram =</span> <span class="st">&quot;none&quot;</span>,</span>
<span id="cb1-31"><a href="#cb1-31" tabindex="-1"></a>        <span class="at">xlab =</span> <span class="st">&quot;&quot;</span>, <span class="at">ylab =</span> <span class="st">&quot;&quot;</span>,</span>
<span id="cb1-32"><a href="#cb1-32" tabindex="-1"></a>        <span class="at">main =</span> <span class="st">&quot;&quot;</span>,</span>
<span id="cb1-33"><a href="#cb1-33" tabindex="-1"></a>        <span class="at">scale =</span> <span class="st">&quot;column&quot;</span>,</span>
<span id="cb1-34"><a href="#cb1-34" tabindex="-1"></a>        <span class="at">margins =</span> <span class="fu">c</span>(<span class="dv">60</span>,<span class="dv">100</span>,<span class="dv">40</span>,<span class="dv">20</span>),</span>
<span id="cb1-35"><a href="#cb1-35" tabindex="-1"></a>        <span class="at">grid_color =</span> <span class="st">&quot;white&quot;</span>,</span>
<span id="cb1-36"><a href="#cb1-36" tabindex="-1"></a>        <span class="at">grid_width =</span> <span class="fl">0.00001</span>,</span>
<span id="cb1-37"><a href="#cb1-37" tabindex="-1"></a>        <span class="at">titleX =</span> <span class="cn">FALSE</span>,</span>
<span id="cb1-38"><a href="#cb1-38" tabindex="-1"></a>        <span class="at">hide_colorbar =</span> <span class="cn">TRUE</span>,</span>
<span id="cb1-39"><a href="#cb1-39" tabindex="-1"></a>        <span class="at">branches_lwd =</span> <span class="fl">0.1</span>,</span>
<span id="cb1-40"><a href="#cb1-40" tabindex="-1"></a>        <span class="at">label_names =</span> <span class="fu">c</span>(<span class="st">&quot;Country&quot;</span>, <span class="st">&quot;Feature:&quot;</span>, <span class="st">&quot;Value&quot;</span>),</span>
<span id="cb1-41"><a href="#cb1-41" tabindex="-1"></a>        <span class="at">fontsize_row =</span> <span class="dv">5</span>, <span class="at">fontsize_col =</span> <span class="dv">5</span>,</span>
<span id="cb1-42"><a href="#cb1-42" tabindex="-1"></a>        <span class="at">labCol =</span> <span class="fu">colnames</span>(mat),</span>
<span id="cb1-43"><a href="#cb1-43" tabindex="-1"></a>        <span class="at">labRow =</span> <span class="fu">rownames</span>(mat),</span>
<span id="cb1-44"><a href="#cb1-44" tabindex="-1"></a>        <span class="at">heatmap_layers =</span> <span class="fu">theme</span>(<span class="at">axis.line =</span> <span class="fu">element_blank</span>())</span>
<span id="cb1-45"><a href="#cb1-45" tabindex="-1"></a>        )</span></code></pre></div>
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Peru<br>Feature:: Mortality rate<br>Value: -1.276106","Country: Peru<br>Feature:: Life expectancy<br>Value:  0.096679","Country: Peru<br>Feature:: Infant mortality<br>Value: -0.225383","Country: Peru<br>Feature:: Children per woman<br>Value: -0.082533","Country: Peru<br>Feature:: Growth rate<br>Value:  0.118453","Country: Peru<br>Feature:: Population aged 65 <br>Value: -0.368390"],["Country: New Zealand<br>Feature:: Pop<br>Value: -0.413610","Country: New Zealand<br>Feature:: Birth rate<br>Value: -0.504009","Country: New Zealand<br>Feature:: Mortality rate<br>Value: -0.590496","Country: New Zealand<br>Feature:: Life expectancy<br>Value:  0.879745","Country: New Zealand<br>Feature:: Infant mortality<br>Value: -0.694935","Country: New Zealand<br>Feature:: Children per woman<br>Value: -0.366859","Country: New Zealand<br>Feature:: Growth rate<br>Value: -0.176263","Country: New Zealand<br>Feature:: Population aged 65 <br>Value: -0.457405"],["Country: Kenya<br>Feature:: Pop<br>Value: 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</center>
<p><em>Note</em>: You can learn more about this dataset and how to
visualize it in the <a href="">dedicated page</a></p>
</div>
<div id="what-for" class="section level1">
<h1>What for</h1>
<hr />
<p>A heatmap is really useful to display a <code>general view</code> of
numerical data, <strong>not</strong> to extract specific data point. In
the graphic above, the huge population size of China and India pops out
for example.</p>
<p><br></p>
<p>A heatmap is also useful to display the result of
<code>hierarchical clustering</code>. Basically, clustering checks which
countries tend to have the same features on their numeric variables, and
therefore which countries are <strong>similar</strong>. The usual way to
represent the result is to use <a
href="https://www.data-to-viz.com/graph/dendrogram.html">dendrograms</a>.
This type of chart can be drawn around the heatmap:</p>
<div class="sourceCode" id="cb2"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb2-1"><a href="#cb2-1" tabindex="-1"></a>p <span class="ot">&lt;-</span> <span class="fu">heatmaply</span>(mat,</span>
<span id="cb2-2"><a href="#cb2-2" tabindex="-1"></a>        <span class="co">#dendrogram = &quot;row&quot;,</span></span>
<span id="cb2-3"><a href="#cb2-3" tabindex="-1"></a>        <span class="at">xlab =</span> <span class="st">&quot;&quot;</span>, <span class="at">ylab =</span> <span class="st">&quot;&quot;</span>,</span>
<span id="cb2-4"><a href="#cb2-4" tabindex="-1"></a>        <span class="at">main =</span> <span class="st">&quot;&quot;</span>,</span>
<span id="cb2-5"><a href="#cb2-5" tabindex="-1"></a>        <span class="at">scale =</span> <span class="st">&quot;column&quot;</span>,</span>
<span id="cb2-6"><a href="#cb2-6" tabindex="-1"></a>        <span class="at">margins =</span> <span class="fu">c</span>(<span class="dv">60</span>,<span class="dv">100</span>,<span class="dv">40</span>,<span class="dv">20</span>),</span>
<span id="cb2-7"><a href="#cb2-7" tabindex="-1"></a>        <span class="at">grid_color =</span> <span class="st">&quot;white&quot;</span>,</span>
<span id="cb2-8"><a href="#cb2-8" tabindex="-1"></a>        <span class="at">grid_width =</span> <span class="fl">0.00001</span>,</span>
<span id="cb2-9"><a href="#cb2-9" tabindex="-1"></a>        <span class="at">titleX =</span> <span class="cn">FALSE</span>,</span>
<span id="cb2-10"><a href="#cb2-10" tabindex="-1"></a>        <span class="at">hide_colorbar =</span> <span class="cn">TRUE</span>,</span>
<span id="cb2-11"><a href="#cb2-11" tabindex="-1"></a>        <span class="at">branches_lwd =</span> <span class="fl">0.1</span>,</span>
<span id="cb2-12"><a href="#cb2-12" tabindex="-1"></a>        <span class="at">label_names =</span> <span class="fu">c</span>(<span class="st">&quot;Country&quot;</span>, <span class="st">&quot;Feature:&quot;</span>, <span class="st">&quot;Value&quot;</span>),</span>
<span id="cb2-13"><a href="#cb2-13" tabindex="-1"></a>        <span class="at">fontsize_row =</span> <span class="dv">5</span>, <span class="at">fontsize_col =</span> <span class="dv">5</span>,</span>
<span id="cb2-14"><a href="#cb2-14" tabindex="-1"></a>        <span class="at">labCol =</span> <span class="fu">colnames</span>(mat),</span>
<span id="cb2-15"><a href="#cb2-15" tabindex="-1"></a>        <span class="at">labRow =</span> <span class="fu">rownames</span>(mat),</span>
<span id="cb2-16"><a href="#cb2-16" tabindex="-1"></a>        <span class="at">heatmap_layers =</span> <span class="fu">theme</span>(<span class="at">axis.line=</span><span class="fu">element_blank</span>())</span>
<span id="cb2-17"><a href="#cb2-17" tabindex="-1"></a>        )</span>
<span id="cb2-18"><a href="#cb2-18" tabindex="-1"></a></span>
<span id="cb2-19"><a href="#cb2-19" tabindex="-1"></a><span class="co"># save the widget</span></span>
<span id="cb2-20"><a href="#cb2-20" tabindex="-1"></a><span class="co"># library(htmlwidgets)</span></span>
<span id="cb2-21"><a href="#cb2-21" tabindex="-1"></a><span class="co"># saveWidget(p, file= &quot;~/Desktop/R-graph-gallery/HtmlWidget/heatmapInter.html&quot;)</span></span></code></pre></div>
<center>
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<br>Value: -0.417218","Country: Kenya<br>Feature:: Life expectancy<br>Value: -1.287874"],["Country: Afghanistan<br>Feature:: Mortality rate<br>Value: -0.221322","Country: Afghanistan<br>Feature:: Infant mortality<br>Value:  1.805110","Country: Afghanistan<br>Feature:: Children per woman<br>Value:  1.346991","Country: Afghanistan<br>Feature:: Birth rate<br>Value:  1.267622","Country: Afghanistan<br>Feature:: Growth rate<br>Value:  1.171011","Country: Afghanistan<br>Feature:: Pop<br>Value: -0.330982","Country: Afghanistan<br>Feature:: Population aged 65 <br>Value: -0.448492","Country: Afghanistan<br>Feature:: Life expectancy<br>Value: -1.480803"],["Country: Bolivia<br>Feature:: Mortality rate<br>Value: -0.432279","Country: Bolivia<br>Feature:: Infant mortality<br>Value:  0.599505","Country: Bolivia<br>Feature:: Children per woman<br>Value:  0.288669","Country: Bolivia<br>Feature:: Birth rate<br>Value:  0.469415","Country: Bolivia<br>Feature:: Growth rate<br>Value:  0.423695","Country: Bolivia<br>Feature:: Pop<br>Value: -0.395684","Country: Bolivia<br>Feature:: Population aged 65 <br>Value: -0.456000","Country: Bolivia<br>Feature:: Life expectancy<br>Value: -0.561551"],["Country: Fiji<br>Feature:: Mortality rate<br>Value: -0.379540","Country: Fiji<br>Feature:: Infant mortality<br>Value: -0.297296","Country: Fiji<br>Feature:: Children per woman<br>Value:  0.020140","Country: Fiji<br>Feature:: Birth rate<br>Value:  0.060577","Country: Fiji<br>Feature:: Growth rate<br>Value: -0.607812","Country: Fiji<br>Feature:: Pop<br>Value: -0.423812","Country: Fiji<br>Feature:: Population aged 65 <br>Value: -0.494296","Country: Fiji<br>Feature:: Life expectancy<br>Value: -0.459412"],["Country: Argentina<br>Feature:: Mortality rate<br>Value: -0.274061","Country: Argentina<br>Feature:: Infant mortality<br>Value: -0.364980","Country: Argentina<br>Feature:: Children per woman<br>Value: -0.145717","Country: Argentina<br>Feature:: Birth rate<br>Value: -0.114639","Country: Argentina<br>Feature:: Growth rate<br>Value: -0.144686","Country: Argentina<br>Feature:: Pop<br>Value: -0.304368","Country: Argentina<br>Feature:: Population aged 65 <br>Value: -0.470044","Country: Argentina<br>Feature:: Life expectancy<br>Value:  0.255562"],["Country: Venezuela<br>Feature:: Mortality rate<br>Value: -1.223367","Country: Venezuela<br>Feature:: Infant mortality<br>Value: -0.348059","Country: Venezuela<br>Feature:: Children per woman<br>Value: -0.137819","Country: Venezuela<br>Feature:: Birth rate<br>Value:  0.041108","Country: Venezuela<br>Feature:: Growth rate<br>Value:  0.181607","Country: Venezuela<br>Feature:: Pop<br>Value: -0.338097","Country: Venezuela<br>Feature:: Population aged 65 <br>Value: -0.378382","Country: Venezuela<br>Feature:: Life expectancy<br>Value:  0.028586"],["Country: Peru<br>Feature:: Mortality rate<br>Value: -1.276106","Country: Peru<br>Feature:: Infant mortality<br>Value: -0.225383","Country: Peru<br>Feature:: Children per woman<br>Value: 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Australia<br>Feature:: Infant mortality<br>Value: -0.711856","Country: Australia<br>Feature:: Children per woman<br>Value: -0.461634","Country: Australia<br>Feature:: Birth rate<br>Value: -0.494274","Country: Australia<br>Feature:: Growth rate<br>Value:  0.234235","Country: Australia<br>Feature:: Pop<br>Value: -0.358177","Country: Australia<br>Feature:: Population aged 65 <br>Value: -0.284344","Country: Australia<br>Feature:: Life expectancy<br>Value:  0.947838"],["Country: New Zealand<br>Feature:: Mortality rate<br>Value: -0.590496","Country: New Zealand<br>Feature:: Infant mortality<br>Value: -0.694935","Country: New Zealand<br>Feature:: Children per woman<br>Value: -0.366859","Country: New Zealand<br>Feature:: Birth rate<br>Value: -0.504009","Country: New Zealand<br>Feature:: Growth rate<br>Value: -0.176263","Country: New Zealand<br>Feature:: Pop<br>Value: -0.413610","Country: New Zealand<br>Feature:: Population aged 65 <br>Value: -0.457405","Country: New Zealand<br>Feature:: Life expectancy<br>Value:  0.879745"],["Country: Canada<br>Feature:: Mortality rate<br>Value: -0.274061","Country: Canada<br>Feature:: Infant mortality<br>Value: -0.682244","Country: Canada<br>Feature:: Children per woman<br>Value: -0.698571","Country: Canada<br>Feature:: Birth rate<br>Value: -0.727896","Country: Canada<br>Feature:: Growth rate<br>Value: -0.186789","Country: Canada<br>Feature:: Pop<br>Value: -0.325466","Country: Canada<br>Feature:: Population aged 65 <br>Value: -0.150713","Country: Canada<br>Feature:: Life expectancy<br>Value:  0.902443"],["Country: Thailand<br>Feature:: Mortality rate<br>Value:  0.200591","Country: Thailand<br>Feature:: Infant mortality<br>Value: -0.458044","Country: Thailand<br>Feature:: Children per woman<br>Value: -0.785449","Country: Thailand<br>Feature:: Birth rate<br>Value: -0.796036","Country: Thailand<br>Feature:: Growth rate<br>Value: -0.965681","Country: Thailand<br>Feature:: Pop<br>Value: -0.239650","Country: Thailand<br>Feature:: Population aged 65 <br>Value: -0.058944","Country: Thailand<br>Feature:: Life expectancy<br>Value:  0.051283"],["Country: Sweden<br>Feature:: Mortality rate<br>Value:  0.522828","Country: Sweden<br>Feature:: Infant mortality<br>Value: -0.748785","Country: Sweden<br>Feature:: Children per woman<br>Value: -0.408718","Country: Sweden<br>Feature:: Birth rate<br>Value: -0.560467","Country: Sweden<br>Feature:: Growth rate<br>Value: -0.424667","Country: Sweden<br>Feature:: Pop<br>Value: -0.399042","Country: Sweden<br>Feature:: Population aged 65 <br>Value: -0.387024","Country: Sweden<br>Feature:: Life expectancy<br>Value:  0.919579"],["Country: France<br>Feature:: Mortality rate<br>Value:  0.569766","Country: France<br>Feature:: Infant mortality<br>Value: -0.733007","Country: France<br>Feature:: Children per woman<br>Value: -0.358961","Country: France<br>Feature:: Birth rate<br>Value: -0.591617","Country: France<br>Feature:: Growth rate<br>Value: -0.692016","Country: France<br>Feature:: Pop<br>Value: 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</center>
<p>Here, Burundi and Angola are grouped together. Indeed they are two
countries in strong expansion, with a lot of children per woman but
still a strong mortality rate.</p>
<p><em>Note</em>: in this heatmap, features are also clusterised. For
instance, birth rate and children per woman are grouped together since
they are highly correlated.</p>
<p><em>Note</em>: hierarchical clustering is a complex statistical
method. You can learn more about it <a
href="https://en.wikipedia.org/wiki/Hierarchical_clustering">here</a>.</p>
</div>
<div id="variation" class="section level1">
<h1>Variation</h1>
<hr />
<ul>
<li><p>We’ve seen in the previous section that a heatmap is often used
to display the result of a clustering algorithm. A common task is to
compare the result with expectations. For instance, we can check if the
countries are clustering according to their continent using a
<code>color bar</code>.</p></li>
<li><p>For a static heatmap, a common practice is to display the
<strong>exact value</strong> of each cell in numbers. Indeed, it is hard
to translate a color into a precise number.</p></li>
<li><p>Heatmaps can also be used for time series where there is a
<strong>regular pattern</strong> in time.</p></li>
<li><p>Heatmaps can be applied to <strong>adjacency
matrices</strong>.</p></li>
</ul>
</div>
<div id="mistake" class="section level1">
<h1>Common mistakes</h1>
<hr />
<ul>
<li>Often need to normalize your data</li>
<li>Use <strong>cluster analysis</strong> and thus permute the rows and
the columns of the matrix to place similar values near each other
according to the clustering</li>
<li>Color palette is important</li>
</ul>
</div>
<div id="related" class="section level1">
<h1>Related</h1>
<hr />
<div class="row">
<div class="col-lg-3 col-md-6 col-sm-6">
<a href="http://www.data-to-viz.com/graph/scatter.html" class="btn btn-primary mybtnrelated" style="margin-bottom:4px;white-space: normal !important;">
<img  src="https://github.com/holtzy/data_to_viz/raw/master/img/section/ScatterPlotSmall.png">
<p class="mytitlerelated">
Scatter plot
</p>
<p class="mytextrelated">
Display the relationship between 2 numeric variables
</p>
</a>
</div>
<div class="col-lg-3 col-md-6 col-sm-6">
<a href="http://www.data-to-viz.com/graph/correlogram.html" class="btn btn-primary mybtnrelated" style="margin-bottom:4px;white-space: normal !important;">
<img  src="https://github.com/holtzy/data_to_viz/raw/master/img/section/CorrelogramSmall.png">
<p class="mytitlerelated">
Correlogram
</p>
<p class="mytextrelated">
Shows the relationship between each pair of numeric variables
</p>
</a>
</div>
<div class="col-lg-3 col-md-6 col-sm-6">
<a href="http://www.data-to-viz.com/graph/connectedscatter.html" class="btn btn-primary mybtnrelated" style="margin-bottom:4px;white-space: normal !important;">
<img  src="https://github.com/holtzy/data_to_viz/raw/master/img/section/ScatterConnectedSmall.png">
<p class="mytitlerelated">
Connected Scatterplot
</p>
<p class="mytextrelated">
Very close from a scatterplot, but link data points with segments
</p>
</a>
</div>
<div class="col-lg-3 col-md-6 col-sm-6">
<a href="http://www.data-to-viz.com/graph/density2d.html" class="btn btn-primary mybtnrelated" style="margin-bottom:4px;white-space: normal !important;">
<img  src="https://github.com/holtzy/data_to_viz/raw/master/img/section/2dDensitySmall.png">
<p class="mytitlerelated">
Density 2d
</p>
<p class="mytextrelated">
One of the best way to avoid overplotting for big sample size
</p>
</a>
</div>
</div>
</div>
<div id="code" class="section level1">
<h1>Build your own</h1>
<hr />
<p>The <a href="https://r-graph-gallery.com/heatmap.html">R</a>, <a
href="https:/python-graph-gallery.com/heatmap/">Python</a>, <a
href="https://www.react-graph-gallery.com/heatmap">React</a> and <a
href="https://d3-graph-gallery.com/heatmap">D3</a> graph galleries are 4
websites providing hundreds of chart example, always providing the
reproducible code. Click the button below to see how to build the chart
you need with your favorite programing language.</p>
<p>
<a href="https://r-graph-gallery.com/heatmap.html" class="btn btn-primary">R
graph gallery</a>
<a href="https://python-graph-gallery.com/heatmap/" class="btn btn-primary">Python
gallery</a>
<a href="https://www.react-graph-gallery.com/heatmap" class="btn btn-primary">React
gallery</a>
<a href="https://d3-graph-gallery.com/heatmap" class="btn btn-primary">D3
gallery</a>
</p>
</div>
</div>

          <section
            id="form"
            style="
              margin-top: 70px;
              padding-bottom: 70px;
              padding-top: 70px;
              background-color: #f8f9fa;
            "
          >
            <div class="container">
              <div
                style="
                  display: flex;
                  flex-direction: column;
                  align-items: center;
                "
              >
                <h2 style="font-size: 44px" class="text-center">
                  Dataviz decision tree
                </h2>
                <p
                  class="text-center"
                  style="max-width: 600px; font-size: 18px"
                >
                  <a href="https://www.data-to-viz.com">Data To Viz</a> is a
                  comprehensive <b>classification of chart types</b> organized
                  by data input format. Get a high-resolution version of our
                  decision tree delivered to your inbox now!
                </p>
                <div
                  style="
                    margin-top: -50px;
                    width: 100%;
                    display: flex;
                    justify-content: center;
                  "
                >
                  <script
                    async
                    data-uid="8010f15fd2"
                    src="https://prodigious-trailblazer-3628.ck.page/8010f15fd2/index.js"
                  ></script>
                </div>
                <br />
                <div class="text-center">
                  <img
                    class="img-fluid"
                    src="../img/poster/poster_small.png"
                    alt="High Resolution Poster"
                    style="max-width: 400px"
                  />
                </div>
              </div>
            </div>
          </section>

           &nbsp;
<hr />
<p style="text-align: center;">A work by <a href="https://www.yan-holtz.com/">Yan Holtz</a> for <a href="https://data-to-viz.com">data-to-viz.com</a></p>

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	<a href="https://twitter.com/r_graph_gallery?lang=en" class="fa fa-twitter"></a>
	<a href="https://www.linkedin.com/in/yan-holtz-2477534a/" class="fa fa-linkedin"></a>
	<a href="https://github.com/holtzy/" class="fa fa-github"></a>
</p>

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